Hide metadata

dc.date.accessioned2023-03-09T16:08:45Z
dc.date.available2023-03-09T16:08:45Z
dc.date.created2022-04-09T13:49:23Z
dc.date.issued2022
dc.identifier.citationAli, Usman Caso, Giuseppe De Nardis, Luca Kousias, Konstantinos Rajiullah, Mohammad Alay, Ozgu Neri, Marco Brunstrom, Anna Di Benedetto, Maria-Gabriella . Large-Scale Dataset for the Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks. Data. 2022, 7(3)
dc.identifier.urihttp://hdl.handle.net/10852/101082
dc.description.abstractUnderstanding radio propagation characteristics and developing channel models is fundamental to building and operating wireless communication systems. Among others uses, channel characterization and modeling can be used for coverage and performance analysis and prediction. Within this context, this paper describes a comprehensive dataset of channel measurements performed to analyze outdoor-to-indoor propagation characteristics in the mid-band spectrum identified for the operation of 5th Generation (5G) cellular systems. Previous efforts to analyze outdoor-to-indoor propagation characteristics in this band were made by using measurements collected on dedicated, mostly single-link setups. Hence, measurements performed on deployed and operational 5G networks still lack in the literature. To fill this gap, this paper presents a dataset of measurements performed over commercial 5G networks. In particular, the dataset includes measurements of channel power delay profiles from two 5G networks in Band n78, i.e., 3.3–3.8 GHz. Such measurements were collected at multiple locations in a large office building in the city of Rome, Italy by using the Rohde & Schwarz (R&S) TSMA6 network scanner during several weeks in 2020 and 2021. A primary goal of the dataset is to provide an opportunity for researchers to investigate a large set of 5G channel measurements, aiming at analyzing the corresponding propagation characteristics toward the definition and refinement of empirical channel propagation models.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleLarge-Scale Dataset for the Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
dc.title.alternativeENEngelskEnglishLarge-Scale Dataset for the Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks
dc.typeJournal article
dc.creator.authorAli, Usman
dc.creator.authorCaso, Giuseppe
dc.creator.authorDe Nardis, Luca
dc.creator.authorKousias, Konstantinos
dc.creator.authorRajiullah, Mohammad
dc.creator.authorAlay, Ozgu
dc.creator.authorNeri, Marco
dc.creator.authorBrunstrom, Anna
dc.creator.authorDi Benedetto, Maria-Gabriella
cristin.unitcode185,15,5,75
cristin.unitnameDIS Digital infrastruktur og sikkerhet
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin2016341
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Data&rft.volume=7&rft.spage=&rft.date=2022
dc.identifier.jtitleData
dc.identifier.volume7
dc.identifier.issue3
dc.identifier.pagecount0
dc.identifier.doihttps://doi.org/10.3390/data7030034
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2306-5729
dc.type.versionPublishedVersion
cristin.articleid34


Files in this item

Appears in the following Collection

Hide metadata

Attribution 4.0 International
This item's license is: Attribution 4.0 International